Erosion Classes Research Articles

Identification needs and placement location of conservation building in upstream area with geographical information system

The upper course of water catchment areas is buffer area for conservation at the watershed. In upstream area there are also regions where also suitable for planting a variety of agriculture commodities. The activity can cause the accurence of erosion and land degradation, so as to encourage of the flow of sediment to major rivers. The sediment carried by the flow of run off is to downstream so that causes silting-up of the grooves river due to sedimentation, that decrease capacity of flow the river and causes overflow of the river so there was a flood. Base on the problem, required building for conservation there is retaining sediment building on a grooves at the upperstream to hold and controling the flow of sediment. Therefor reguired to identification of the needs and right location to exact placement of the retaining sediment building. Because the nature of the land on the upstream area are hilly condition used geographical information system (GIS) to assist in identification of the needs and to determination of site the retaining sediment building. The purpose of the research is to prevent and control the flow of sediment that accur in upstream area and flow into the major river. The objective of the study is to understand the needs and appropriate location to placement of retaining sediment building in the watershed. Research methods that used is using geographical information system which combined with class and level of erosion and the technical requirement of retaining sediment building. The result showing that geographical information system can help in assignment the appropriate site of retaining sediment building in the grooves of upstream areas. According 29 catchment areas in the watershed, 17 of the region in accordance to putting retaining sediment building and 12 region other not appropriate. The number of retaining sediment building that can built in the watershed there was 22 location/points.

Quantitative assessment of climate change impacts onto predicted erosion risks and their spatial distribution within the landcover classes of the Southern Caucasus using GIS and remote sensing

The objectives of this research are the following: quantitative assessment of erosion-prone areas, assessment of the impacts of climate change on future erosion risks and quantification of erosion risks in relation to landcover classes. The practical value of this study is that it promotes a collaborative planning and decision-making tool for the mitigation of erosion risks and consequences which are inevitable for the Southern Caucasus. The selected study area in the Southern Caucasus is the Ismayilly District. The scientific novelty lies in the fact that it considers the aspects of climate change in the prediction of erosion risks. The Universal Soil Loss Equation was used for the prediction of soil loss rates. Out of 2559 km2, 292 km2 were predicted as critical erosion classes with soil loss rates of more than 10 tons/ha/year. Precipitation impacts calculated by means of theHadGEM2-AOclimate change model to erosion processes also showed an increase in soil loss rates. The quantification of predicted erosion related to landcover revealed a significant variation of critical erosion classes within bare lands (5–10 ton/ha/year to 6.21 km2, 10–20 ton/ha/year to 11.90 km2, 20–50 ton/ha/year to 28.24 km2, 50–100 ton/ha/year to 15.44 km2, 100–200 ton/ha/year to 0.75 km2). The quantification of erosion rates related to landcover classes showed their highest spatial distribution variability within barelands (62.55 km2 out of total 71 km2) and grasslands (339.44 km2 out of total 895 km2). Significant areas of stressed vegetation with low NDVI values (0.1–0.2) were observed to be 259.51 km2 within croplands affected by intensive agricultural activities which reduced soil productivity over years.

Test of the RUSLE and Key Influencing Factors Using GIS and Probability Methods: A Case Study in Nanling National Nature Reserve, South China

The main purposes of the study were to test the performance of the Revised Universal Soil Loss Equation (RUSLE) and to understand the key factors responsible for generating soil erosion in the Nanling National Nature Reserve (NNNR), South China, where soil erosion has become a very serious ecological and environmental problem. By combining the RUSLE and geographic information system (GIS) data, we first produced a map of soil erosion risk at 30 m‐resolution pixel level with predicted factors. We then used consecutive Landsat 8 satellite images to obtain the spatial distribution of four types of soil erosion and carried out ground truth checking of the RUSLE. On this basis, we innovatively developed a probability model to explore the relationship between four types of soil erosion and the key influencing factors, identify high erosion area, and analyze the reason for the differences derived from the RUSLE. The results showed that the overall accuracy of image interpretation was acceptable, which could be used to represent the currently actual spatial distribution of soil erosion. Ground truth checking indicated some differences between the spatial distribution and class of soil erosion derived from the RUSLE and the actual situation. The performance of the RUSLE was unsatisfactory, producing differences and even some errors when used to estimate the ecological risks posed by soil erosion within the NNNR. We finally produced a probability table revealing the degree of influence of each factor on different types of soil erosion and quantitatively elucidated the reason for generating these differences. We suggested that soil erosion type and the key influencing factors should be identified prior to soil erosion risk assessment in a region.

Coastal Vulnerability to Erosion Using a Multi-Criteria Index: A Case Study of the Xiamen Coast

The assessment of coastal vulnerability to erosion is urgently needed due to increasing coastal erosion globally. Based on the coastal characteristics of the Xiamen artificial coastline, which accounts for more than 80% of the coastline in this area, this study provides an integrated approach based on a multi-criteria index. The evaluation index system of the local coastal vulnerability to the erosion of Xiamen includes 12 indexes based on natural (coastal characteristics, coastal forcing), and socio-economic factors (coastal infrastructure, disaster reduction). The spatial differentiation characteristics of the coastal vulnerability to erosion along the Xiamen coast (2018) have been quantitatively assessed with the aid of GIS (Geographic Information System) and RS (Remote Sensing) technology. The results show that the very high vulnerability, high vulnerability, medium vulnerability, low vulnerability and very low vulnerability areas of coastal erosion accounted for 4.6%, 30.5%, 51.6%, 12.5% and 0.8% of the Xiamen coast, respectively. The coastal vulnerability to erosion classes of artificial coasts is significantly higher than those of natural coasts. This difference is mainly controlled by the coastal slope and coastal buffer ability. The results of the evaluation are basically consistent with the present situation. The rationality of the index system and the applicability of the theoretical method are well explained. The evaluation model constructed in this study can be extended to other areas with high ratios of artificial coasts.

Spatial assessment of soil erosion in a hilly watershed of Western Nepal

Soil erosion is a serious problem mankind is facing today as it has been continuously degrading the quality and standard of lives across the globe. Being a hilly country with undulating topography with steeper slopes accompanied with heavy rainfall, Nepal is predisposed to natural hazards including soil erosion. This paper attempts to model the soil erosion rate in the Aringale Khola Watershed of middle hills of Nepal with the judicious use of geographic information system (GIS) and revised universal soil loss equation (RUSLE) techniques. RUSLE was used in ArcGIS environment, taking rainfall-runoff (R), soil erodibility (K), topography (LS), crop management (C) and conservation support practice (P) factors as primary inputs. A total of nine soil erosion classes were observed; soil erosion rates ranging from 0.03 to 100.33 t/ha/year with a mean soil rate of 11.17 t/ha/year. GIS analysis depicted that 36.93% (1256.28 ha) of the total watershed area fell in the severe erosion classes whereas the remaining 63.07% (2145.56 ha) were less severe. A major part of the watershed, particularly areas with higher elevations and steep slopes, are degraded and needs urgent conservation measures. This study is a first attempt to model soil erosion distribution in the Aringale Khola Watershed and has very good potential to be used for soil erosion prediction in similar watersheds in the middle hills of Nepal.

Mapping soil degradation using remote sensing data and ancillary data: South-East Moravia, Czech Republic

ABSTRACT Data on the real extent of soil that is degraded by erosion represent important information for the purposes of conservation policy. However, this type of data is rarely available for large areas. A remote-sensing-based method for identifying of eroded areas at the regional scale has been tested using a combination of time series of free access Sentinel-2 image data, airborne orthoimages and ground-truth data. The unsupervised classification ISODATA of the Sentinel-2A images has been performed. The minimum distance method has been applied for the assignment of unsupervised classes to four erosion classes using the ground-truth data. The automatic classification of eroded soils achieved an overall accuracy of 55.2% for three distinguished classes. An accumulated class has been eliminated as no unsupervised classes were assigned to this erosion class. A simplified classification of two classes (strongly eroded and other soils) reached an accuracy of 80.9%. The overall accuracy of the simplified classification increased to 86.9% after the visual refinement using orthoimages. This study shows the potential of the tested approach to produce valuable data on actual soil degradation by erosion. The limitations of the method are related to the soil cover variability, masking effect of clouds, vegetation or litter and the spectral separability of individual classes.

An improved RUSLE/SDR model for the evaluation of soil erosion

The accurate assessment of soil erosion is key to assess environmental parameters, such as the reduction in soil fertility, the increase in flood risk, the loss of nutrients, and degradation of water quality. In this study, we developed a methodology using the Revised Universal Soil Loss Equation (RUSLE) with the sediment delivery ratio (SDR) to estimate the annual amount of soil erosion and sediment yield in the Nozhian watershed (western Iran). The weighted total least-squares (WTLS) algorithm was applied to generate the rainfall–runoff erosivity surface using rainfall data and a digital elevation model (DEM) instead of traditional interpolation methods. The results demonstrated that the obtained sediment yield by the RUSLE/SDR model was approximately 802,000 tons per year. More than half of the watershed (61.6%) belonged to the high and severe erosion classes (20–100 t/ha year), and the mean soil erosion rate in the study area was 89.32 t/ha year. Several landslides extracted using a Google Earth map by expert interpretation were exactly consistent with areas that had high erosion rates based on the RUSLE results. This compatibility implies the compatibility between the results and reality. According to the statistical analysis, topographic features, especially slope steepness, had the greatest effect on the rate of soil erosion in the region. The results of our RUSLE/SDR analysis were also compared with the reported results from the Modify Pacific Southwest Interagency Committee (MPSIAC), Erosion Potential method (EPM), and Hydrophysical model. In situ data from the measured annual sediment yield during a 40-year interval from a hydrometric station were used for the accuracy analysis. The comparison indicated improvement in the accuracy of our approach by up to 65% in comparison to other reported results. These results can surely aid in the implementation of soil management and conservation practices to reduce soil erosion in the Nozhian watershed.

Investigation of likely effects of land use planning on reduction of soil erosion rate in river basins: Case study of the Gharesoo River Basin

We investigated the effects of land use planning on reduction of soil erosion rate in the Gharesoo River Basin, Golestan Province, Iran. For this, the Revised Universal Soil Loss Equation (RUSLE) was used in conjunction with Geographic Information System (GIS) to model potential soil erosion. The average potential soil erosion in the river basin was 18.65 t ha−1 yr−1, with a standard deviation of 33.88 t ha−1 yr−1. The severe and very severe erosion classes comprised 8% and 4% of the river basin, respectively. We found that all areas with severe and very severe erosion were located in agricultural land. Assessing the impacts of land use and slope confirmed importance of interaction between these factors in increasing soil erosion, especially in agricultural areas with steep slopes. We applied a land use planning to control and reduce soil erosion rate, with a specific focus on agricultural areas. For this purpose, the Multi-Criteria Evaluation (MCE) and Multi-Objective Land Allocation (MOLA) were implemented for agriculture, urban and industrial development, and afforestation. We used the output land use map from MOLA in the RUSLE model. The results showed a significant reduction of average potential soil erosion equal to 25.6% (from 18.65 t ha−1 yr−1 to 13.86 t ha−1 yr−1) when the MOLA land use plan was followed. Also, the area impacted by severe and very severe erosion classes were reduced by 25.50% and 42.59%, respectively. The results of this research emphasized that implementation of land use planning in the Gharesoo River Basin is helpful in controlling soil erosion. The method presented in this study can be a basis for sustainable and comprehensive management of river basins.

ПІДВИЩЕННЯ БІОРІЗНОМАНІТТЯ РОСЛИННИХ ФОРМАЦІЙ ПІД ЧАС ЗЕМЛЕУСТРОЮ АГРОЛАНДШАФТУ

Проаналізовано сучасні світові літературні джерела, що висвітлюють питання підвищення біорізноманіття агроландшафтів. Встановлено, що питання є актуальним, оскільки підтримання різноманітності видів живих елементів екосистеми є обов'язковим для формування стійких територій. Зроблено висновок, що світові дослідження доводять – відновлення стійкості агроекосистем шляхом зменшення розораності території та збільшення біорізноманіття веде до пом'якшення наслідків зміни клімату шляхом створення агроландшафтів, близьких до природних. Дослідження проведено на площі землекористування в межах Великохайчанської сільської ради Овруцького району Житомирської області, що розташована на території Словечансько-Овруцького кряжу. Встановлено, що досліджувана територія різноманітна за рельєфом, ґрунтовим покривом та рівнем перезволоження. Під час формування травосумішей для залуження схилів враховано ступінь еродованості ґрунтів та біологічні особливості рослин. Під час облаштування сіножаті враховано чутливість рослин до зростання на перезволожених або заболочених територіях. На основі зіставлення агроекологічних властивостей ґрунтового покриву і біологічних особливостей багаторічних трав встановлено, що для сірих та ясно-сірих опідзолених ґрунтів досліджуваного агроландшафту найпридатнішою є травосуміш, в якій питома вага багаторічних трав для залуження схилів становить: бобових – 25 %, злакових – 75 %. Для створення сіножаті на глейових ґрунтах відповідно – 15 і 85 %.

Modelagem da erosão hídrica nas bacias hidrográficas dos rios Lontra e Manoel Alves Pequeno, Tocantins

Water erosion is one of the main factors that lead to the process of soil degradation, with impacts ranging from reducing productivity to losses of natural resources. Thus, this work aimed to estimate soil losses performing RUSLE model and to verify the effect of changes in land use changes, from 1990 to 2007, in the watersheds of the rivers Lontra and Manoel Alves Pequeno,Tocantins State-Brazil. Water erosion in the river Lontra ranged from “slight” (51.3%) in the central region of the basin (dominance of flat relief and forest land use), to “extremely high” (24.6%), in the range that goes from the north to the west (dominance of pasture land use and more declining relief). In the watershed of Manoel Alves Pequeno the erosion class “slight” (52%) was distributed along the basin, due to most soils had low erodibility and with most of the area covered by cerrado. While the “extremely high” class (6.7%), occurred in the northern and western part due to pasture land use, and in the eastern part due to the greater slope. Temporal evaluation of soil loss evidenced that there were no significant variations in the period studied. However, in the watershed of river Lontra, from 2000 to 2007, occurred a 0.3% reduction of the “extremely high”; at the wathershed Manoel Alves Pequeno, from 1990 to 2007, there was a gradual increase in the soil erosion rate.

Study and recognition of erosion characteristics of perennial and ephemeral rivers in Tehran province

In the current study, at the first step, the hydrographic net of province rivers was provided based on topography map and hydrographic net from Tamab Company of Iran. Based on these definitions, the whole of Tehran province area was divided into 5 different areas. Based on these definitions, the whole of Tehran province area was divided into 25 different areas. In this study, the areas comprise 415 streams, and long in about 3038 part that 55.5% area had low sensitive to erosion, 49.82 % area had moderate to erosion and 44.63% area had highly sensitive to erosion. Based on the geological study (Alluvial- Stone), 64.72% of the area was categorized in alluvial class and 35.28% area was categorized in stone class. Based on sediments concentration, 26.61% area ranked in low concentration class, 17.05% area was ranked in moderate concentration class and finally, 57.34% area was ranked in high concentration class. Finally, it in view of bed- marginal erosion, about 63.9% were grouped in marginal erosion class and about 36.10% was grouped in bed erosion class.

RUSLE erodibility of heavy‐textured soils as affected by soil type, erosional degradation, and rainfall intensity: A field simulation

AbstractSoil erosion is a serious problem world‐wide for the environment or humankind, exacerbating land degradation. However, little systematic knowledge is available about the erodibility of various types of soils at different erosional degradation levels, especially at the field scale. In this research, the spatiotemporal variations of the erodibility for 5 soil types (calcic luvisol, ferric luvisol, plinthic alisol, plinthic acrisol, and acric ferralsol) from temperate to tropical climate were investigated with field rainfall simulation experiments on prewetted bare fallow heavy‐textured soils (silty clay loam, silty clay, and clay) derived separately from loess deposits, quaternary red clays, and basalt. The experiments were performed in 3 erosion classes (noneroded, moderately eroded, and very severely eroded) and at 2 rainfall intensities (45 and 90 mm hr−1). Soil erodibility was represented by the K factor of the Revised Universal Soil Loss Equation. Soil erodibility was the lowest for the ferralsols among all the soil types and was significantly lower in the very severe than in the no or moderate erosion classes. Soil erodibility tended to be larger at the high than at the low rainfall intensity (p < .05) except for the very severely eroded luvisols, and their difference between rainfall intensities in the erodibility varied with rainfall duration. Soil erodibility could be well predicted by the combination of illite, dry aggregate stability, and amorphous aluminium oxides (adjusted R2 = .51, p < .001), and its temporal variations were significantly related with particle density, 1.4‐nm intergrade mineral, and capillary porosity (p < .05). Furthermore, soil properties selected to account for soil erodibility varied with rainfall intensity. The integrated data indicated that soil erodibility was mainly influenced by clay minerals at the region scale and soil degradation degree at the pedon scale.

Quantification of soil loss in various lithological areas of the western Middle Atlas Central: application to the Ras-Elma, Tamelalet and Sebab watershed (Tigrigra watershed, Morocco)

The present study proposes to evaluate the extent of erosion according to the lithology in three sub-watersheds (Ras Elma, Sebab and Tamelalet) belonging to the Tigrigra basin and evolving in humid climatic context. The methodology adopts the revised universal soil loss equation (RUSLE). The results obtained make it possible to establish erosion class maps via GIS. A clear spatial difference in soil loss is observed, between the three sub-basins and in proportion to the lithology: on average 42.15 t/ha/year on Paleozoic schistose soils, against 17.06 t/ha/year on carbonate substrates Mesozoic and 8.46 t/ha/year on quaternary basalts. Correlations between soil loss and RUSLE factors are established. Soil infiltration regimes on different substrates are studied.

Estimation of Soil Erosion in Rodnei Mountains National Park Using G.I.S. Technique

Abstract Erosion is one of the biggest and most widely spread forms of soil degradation, having an impact on both the surrounding environment and the economical one as well. According to a recent study from 2014-2015 by the Common Research Center an estimate of approximately 11.4% of the EU’s territory has been affected by the erosion process in moderate to high levels, the soil’s erosion rate being higher than 5t/ha/year. A significant part of Romania’s surface feels the negative effects of the soils degradation, erosion being the most widely spread long-term complex phenomena. Identifying as exactly as possible the areas with erosion risk is recommended in order to intervene with measures of consolidation, leveling, terrain modeling and other hydro-improving constructions. For this reason, for the studied area, Rodnei Mountains National Park (Maramureș County, Bistrita-Nasaud County), having a surface of 47.177 ha, the soil’s erosion has been modeled via the USLE model, developed by Motoc in 1979, taking into consideration all the climate conditions specific to Romania. Following the implementation of the G.I.S environment model, the soil’s erosion estimate values have been obtained, subsequently being divided in 8 classes of erosion, losses of soil less than 0.5t/ha/year representing 89.3% out of the park’s total surface. Researching the model’s obtained results and comparing them to existing values of soil erosion, locally and nationally, we can draw the conclusion that the results of the USLE model are truthful, and that the model can be successfully used in the studied area. Thereby, the study has targeted the determination of vulnerabilities at the erosional processes and vulnerabilities to erosion, the risk of erosion susceptibility being assessed.

Spatial estimation of soil erosion risk using RUSLE/GIS techniques and practices conservation suggested for reducing soil erosion in Wadi Mina watershed (northwest, Algeria)

The Wadi Mina Watershed, western area of Algeria is characterized by rare and irregular rains and a fragile and weak vegetable cover. The sediments resulting from erosion are transported and contributed to silting dam Sidi Mhamed Benaouda. The combination of the thematical maps of the various erosive factors according to the Revised Universal Soil Loss Equation (RUSLE) in SIG by ArcGIS 10.2 software provided a reliable forecast of the annual rates of soil loss by delimiting the areas prone to erosive risk in the catchment above mentioned. The estimated potential average annual soil loss is 11.2 t/ha/yr., and the potential erosion rates from recognized erosion classes ranged from 0.0 to plus 100 t/ha/yr. About 50% of the catchment area was predicted to have very low to low erosion risk, with soil loss between 0 and 7.4 t/ha/yr. Erosion risk is moderate over 13.9% of the catchment, where calculated soil loss is between 7.4 and 12 t/ha/yr. Erosion risk is high to dangerous over 36.1% of the catchment, where calculated soil loss is more than 12 t/ha/yr. According to this study, it appeared clearly that we must intervene quickly by using reliable and effective conservation techniques.

Assessment of Soil Degradation by Erosion Based on Analysis of Soil Properties Using Aerial Hyperspectral Images and Ancillary Data, Czech Republic

The assessment of the soil redistribution and real long-term soil degradation due to erosion on agriculture land is still insufficient in spite of being essential for soil conservation policy. Imaging spectroscopy has been recognized as a suitable tool for soil erosion assessment in recent years. In our study, we bring an approach for assessment of soil degradation by erosion by means of determining soil erosion classes representing soils differently influenced by erosion impact. The adopted methods include extensive field sampling, laboratory analysis, predictive modelling of selected soil surface properties using aerial hyperspectral data and the digital elevation model and fuzzy classification. Different multivariate regression techniques (Partial Least Square, Support Vector Machine, Random forest and Artificial neural network) were applied in the predictive modelling of soil properties. The properties with satisfying performance (R2 > 0.5) were used as input data in erosion classes determination by fuzzy C-means classification method. The study was performed at four study sites about 1 km2 large representing the most extensive soil units of the agricultural land in the Czech Republic (Chernozems and Luvisols on loess and Cambisols and Stagnosols on crystalline rocks). The influence of site-specific conditions on prediction of soil properties and classification of erosion classes was assessed. The prediction accuracy (R2) of the best performing models predicting the soil properties varies in range 0.8–0.91 for soil organic carbon content, 0.21–0.67 for sand content, 0.4–0.92 for silt content, 0.38–0.89 for clay content, 0.73–089 for Feox, 0.59–0.78 for Fed and 0.82 for CaCO3. The performance and suitability of different properties for erosion classes’ classification are highly variable at the study sites. Soil organic carbon was the most frequently used as the erosion classes’ predictor, while the textural classes showed lower applicability. The presented approach was successfully applied in Chernozem and Luvisol loess regions where the erosion classes were assessed with a good overall accuracy (82% and 67%, respectively). The model performance in two Cambisol/Stagnosol regions was rather poor (51%–52%). The results showed that the presented method can be directly and with a good performance applied in pedologically and geologically homogeneous areas. The sites with heterogeneous structure of the soil cover and parent material will require more precise local-fitted models and use of further auxiliary information such as terrain or geological data. The future application of presented approach at a regional scale promises to produce valuable data on actual soil degradation by erosion usable for soil conservation policy purposes.

Application of SWAT in an Indian river basin for modeling runoff, sediment and water balance

The present study integrated remote sensing derived products, gridded precipitation and temperature data, and the Soil and Water Assessment Tool (SWAT) within a geographic information system modeling environment to evaluate the hydrology, sediment yield and water balance for a medium-sized Ken basin of Central India. The entire basin was divided into 10 sub-basins comprising 143 hydrological response units on the basis of unique land cover, soil and slope classes using the SWAT model. Monthly and daily calibrated (1985–1995) and validated (1996–2005) SWAT model used the observed discharge and sediment data of the Banda site of the Ken basin. The runoff simulation was good on daily basis (R 2 = 0.766 and 0.780 for calibration and validation period, respectively) and was further improved (very good) on monthly basis (R 2 = 0.946 and 0.959 for calibration and validation period, respectively). The sediment simulation was considerable on daily basis (R 2 = 0.429 and 0.379 for calibration and validation period, respectively) and was further improved (good) on monthly basis (R 2 = 0.748 and 0.721 for calibration and validation period, respectively). The water balance study of the basin showed that evapotranspiration is more predominant accounting for about 44.6% of the average annual precipitation falling over the area. The average annual sediment yield of the basin was found to be 15.41 t/ha/year, which falls under high erosion class.

Land use capacity and environment services

The increasing demand for food resulting from demographic growth has required more productive agropastoral practices. Consequently, new areas were selected for agropastoral production in an arbitrary way, disregarding land use capacity. This ends up in acceleration of degradation processes, mainly those related to water erosion. In this context, the system of land use capacity proposes the classification of maximum use allowed for land of a rural property or of a hydrographic sub-basin, in an attempt to make sustainable plans of use and management of natural resources. Concerning current use of land, the system indicates the sites where there are conflicts in use in relation to their use capacity. Thus, it is possible to propose measures to adapt land use to its use capacity. Therefore, in this study, the classes of land use capacity at the hydrographic sub-basin of Córrego Pedra Branca, in Alfenas, in the state of Minas Gerais, were evaluated. For that purpose, the following soil parameters were evaluated: effective depth, water permeability, texture, declivity, erosion class, base saturation, effective and potential cationic exchange capacity, and aluminum saturation. Soil analyses presented values of base saturation and of low capacity of effective and potential cationic exchange, which illustrate the low natural fertility of these soils, as well as aluminum saturation level harmful to most cultures. Thus, land use would be restricted to low impact, permanent crops, silvicultures, associated agrosilvipastoral system with conservationist management techniques, as, for example, direct seeding, soil correction and fertilization, and reforestation of permanent preservation areas

Identification of Critical Erosion Prone Areas using Remote Sensing and GIS: A Case Study of Sarada River Basin

Background/Objectives: Developed an integrated soil erosion model utilizing RS and GIS approach and mapped for prioritization of critical soil erosion prone areas in a watershed. Methods/Statistical Analysis: The geomorphologic parameters of the watershed have been extracted using Arc-GIS software. In order to evaluate effectively for the soil erosion prone areas, the selected basin has been divided into 143 micro-watershed basins. The micro basins were analyzed using Universal Soil Loss Equation (USLE) soil loss based on annual basis has been assessed for the entire basin. Findings: The soil erosion estimation in a river basin has significant impact on reduction of the reservoir capacities on downstream side if they are situated at the downstream side. In the present study, the soil erosion has been estimated and identified for soil erosion based on their classification. Accordingly, the selected basin has five main categories of soil loss varying from 5 ton per ha per year to more than 80 ton per ha per year. The results obtained based on the present findings, it can be inferred that the Sarada basin has 12.12% area is prone for soil loss of more than 80 ton per ha per year which is under very severe erosion class, 40-80 ton per ha per year under severe class, 11.95% under very high class and 3.10% under high class and 27.78% under moderate class apart from 36.37% under not affected areas for soil erosion. Remote Sensing (RS) technology and Geographic Information System (GIS) were utilized to create and spatially establish the data and maps were generated for soil erosion modeling in the selected region. Applications/Improvements: In the present study, soil erosion has been estimated and critical prone areas for soil loss in a watershed basin that have been generated using RS and GIS.

Quantitative estimation of soil surface erosion in a mountain catchment (Gemenea, Eastern Carpathians)

This study aims to estimate soil removal via sheet erosion in a mountain catchment and highlight the stabilizing role of vegetation on sloping land. Spatial representation of the results was performed through the implementation of GIS techniques. The estimation method used is ROMSEM, which is based on six factors that can be separated into two groups, i.e. i) factors that trigger erosion (rainfall erosivity, topography, soils) and ii) factors controlling erosion (vegetation, anti-erosion measures). These factors constitute the database which generated the maps of potential and effective soil erosion. Based on our results, mean potential erosion is very high, 99.64 t ha -1 yr -1 respectively, and thereby falls into the severe erosion class. Mean effective erosion indicates current soil loss and falls within the insignificant erosion class, with 0.98 t ha -1 yr -1 , which suggests that at the catchment scale, soil is eroded at a rate of 7620 t yr -1